Data and Information Management
Getting the data and information right is key to delivering BI and analytics. This track for technologists looks in detail at how to best use capabilities like data warehousing, BI platforms, data integration and data quality tools, to build the right foundation.
Tutorial: Basics of Data Warehouse and Data Integration for Business Intelligence
05 February, 2013 (08:00 - 08:45)
A tutorial introducing you to terms and basic architecture for integrating and transforming transactional data into analytic stores like your data warehouse. • What are the fundamentals of data warehousing architectures? • What are the components of a basic data integration architecture for BI? • What types of tools fit where?
To The Point: How to Get Started With MDM
05 February, 2013 (14:00 - 14:30)
So you think your organization needs to adopt master data management (MDM), but you don't know where to begin. The business case is not obvious for MDM, and no one is listening to your calls for help. How do you go about figuring out when and if your organization is ready for MDM? Start here. • Under what conditions is MDM most likely to appear? • How can you identify when and where MDM is for your organization? • How can you assess whether you and your team are ready to start MDM?
To The Point: Big Data: Insight from the Trenches
05 February, 2013 (15:45 - 16:15)
Gartner conducted field research of 22 end-user organizations across various industries to find out about their successes and failures with big data projects. You will learn about the current state of big data adoption, and Gartner recommendations on the realistic strategy for big data analytics initiatives. • What is the state of big data analytics adoption in the end-user organizations? • What are the typical issues faced by big data projects? • What are the key success factors of big data analytics?
To The Point: The Promise of In-Memory Computing: It's Not Just About Speed
06 February, 2013 (08:30 - 09:00)
DRAM is the new disk! Not only does in-memory computing (IMC) give a performance boost to analytics, but it also enables "unthinkable" applications, combining event processing, analysis and transactions. Leveraging IMC-disruptive innovation to improve efficiency and build defensible business advantage is an opportunity user organizations must not miss • What is in-memory computing and how will it deliver business value? • How will IMC technologies evolve to challenge traditional data management? • How will user organizations take advantage of IMC?
To The Point: MapReduce and Big Data Descend on the DW – What is All the Fuss About?
06 February, 2013 (14:30 - 15:00)
Big data and its associated tools will change the infrastructure of the EDW and require managers to examine how they manage data in the future. One thing is for sure – you will be supporting organization-wide use of MapReduce to support big data initiatives. You need to understand how this will affect your organization and change your data warehouse. • What new tools will be used to support big data and why will they change the DW? • What do MapReduce and Hadoop do and what infrastructure do they need?
Building Trust In Your Analytics: Data Quality Trends and Best Practices
06 February, 2013 (15:15 - 16:15)
Changes in the types of data being consumed and analytic applications being deployed are driving new and significant data quality challenges. While use and capability of technology is evolving, you must also engage the proper people, develop the required skills, and establish specific roles to achieving substantial progress in data quality improvement. • How are data quality issues changing with the evolution of analytics? • What key data quality practices must organizations adopt? • Where do data quality tools add value and how will the market evolve?
Achieving Enterprise Metadata Management: Key To Making EIM Work
07 February, 2013 (09:00 - 10:00)
Metadata provides the answers to the “who, what, where, when, why and how” questions about master data to promote understanding, consistency, compliance, sharing, and use. Here we explore the world of metadata and possible strategies for enabling EIM, data warehousing and BI. • What is enterprise metadata management and how does it support DW? • How does enterprise metadata management enable an Information Capabilities Framework? • What are the types of metadata sources and strategies?
DBMS Architecture for Data Warehousing: Future Choices
07 February, 2013 (10:30 - 11:30)
DW infrastructure is anything but dull. Gartner sees clients re-architecting server infrastructure from a Unix legacy to Linux X86 or Windows as an option. They then focus on sizing DBMS workloads and assessing the HA requirement. Increasingly, client are also reviewing virtualization for DBMS, not just for consolidation but also portability. • What are the best practices for deploying ERP and DW infrastructure? • How to modernize DBMS platforms for data warehousing? • How does virtualization affect data warehouses?